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--- |
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license: apache-2.0 |
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base_model: google/mt5-small |
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tags: |
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- summarization |
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- generated_from_trainer |
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datasets: |
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- xsum |
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metrics: |
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- rouge |
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model-index: |
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- name: mt5-small-finetuned-amazon-en-es |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: xsum |
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type: xsum |
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config: default |
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split: validation |
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args: default |
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metrics: |
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- name: Rouge1 |
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type: rouge |
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value: 0.0706 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# mt5-small-finetuned-amazon-en-es |
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This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the xsum dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.4800 |
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- Rouge1: 0.0706 |
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- Rouge2: 0.0067 |
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- Rougel: 0.058 |
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- Rougelsum: 0.0654 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5.6e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:| |
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| No log | 1.0 | 13 | 7.7221 | 0.0369 | 0.0 | 0.0369 | 0.0366 | |
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| No log | 2.0 | 26 | 7.1952 | 0.0448 | 0.0 | 0.0452 | 0.0449 | |
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| No log | 3.0 | 39 | 6.5146 | 0.0442 | 0.0 | 0.0443 | 0.044 | |
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| 12.6754 | 4.0 | 52 | 6.2530 | 0.0745 | 0.008 | 0.0636 | 0.0679 | |
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| 12.6754 | 5.0 | 65 | 6.0200 | 0.0745 | 0.0069 | 0.0642 | 0.0693 | |
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| 12.6754 | 6.0 | 78 | 5.7336 | 0.0706 | 0.0067 | 0.058 | 0.0654 | |
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| 12.6754 | 7.0 | 91 | 5.5400 | 0.0706 | 0.0067 | 0.058 | 0.0654 | |
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| 9.1744 | 8.0 | 104 | 5.4800 | 0.0706 | 0.0067 | 0.058 | 0.0654 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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